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Titlebook: Complex Networks & Their Applications XII; Proceedings of The T Hocine Cherifi,Luis M. Rocha,Murat Donduran Conference proceedings 2024 The

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樓主: Eschew
41#
發(fā)表于 2025-3-28 17:51:52 | 只看該作者
Consumer Behaviour Timewise Dependencies Investigation by?Means of?Transition Graphhavioural analysis of the whole population. One of them is the problem of temporal peculiarities of consumer behaviour, for instance, how to find those, who react on some critical events faster than the others. It could be useful for identifying a focus-group which would show the tendency and help t
42#
發(fā)表于 2025-3-28 19:53:53 | 只看該作者
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發(fā)表于 2025-3-29 01:39:55 | 只看該作者
44#
發(fā)表于 2025-3-29 05:24:46 | 只看該作者
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發(fā)表于 2025-3-29 10:29:12 | 只看該作者
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發(fā)表于 2025-3-29 11:49:39 | 只看該作者
47#
發(fā)表于 2025-3-29 19:02:33 | 只看該作者
Time-Dynamics of?(Mis)Information Spread on?Social Networks: A COVID-19 Case Study We employ the CoVaxxy dataset, which encompasses COVID-19 vaccine-related tweets, and classify tweets as reliable/unreliable based on non-credible sources/accounts. We construct separate networks for retweets, replies, and mentions, applying centrality metrics (degree, betweenness, closeness) to as
48#
發(fā)表于 2025-3-29 21:05:10 | 只看該作者
49#
發(fā)表于 2025-3-30 00:16:20 | 只看該作者
A Tale of?Two Cities: Information Diffusion During Environmental Crises in?Flint, Michigan and?East e years to garner national attention. Understanding the spread of information from local to national scales is important, as this spread is often necessary to receive recognition and resources. One way to understand these dynamics is to use information diffusion models, which have been used to inves
50#
發(fā)表于 2025-3-30 06:30:26 | 只看該作者
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